添加比例切分器节点
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Dontdrunk
@@ -64,6 +64,9 @@
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## 📈 版本历史
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### 最新版本
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- **v3.0.0**（2025-09-05）
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- 添加比例切分器节点
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- **v2.9.1**（2025-09-04）
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- 删除DD采样器节点，它已经不适用最新的CommyUI了
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@@ -11,6 +11,7 @@ from .node.model_switcher import NODE_CLASS_MAPPINGS as MODEL_SWITCHER_NODES
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from .node.condition_switcher import NODE_CLASS_MAPPINGS as CONDITION_SWITCHER_NODES
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from .node.latent_switcher import NODE_CLASS_MAPPINGS as LATENT_SWITCHER_NODES
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from .node.image_stroke import NODE_CLASS_MAPPINGS as IMAGE_STROKE_NODES
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from .node.image_splitter import NODE_CLASS_MAPPINGS as IMAGE_SPLITTER_NODES
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# 导入Qwen-MT翻译节点
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from .extensions.Qwen_MT.nodes import NODE_CLASS_MAPPINGS as QWEN_MT_NODES
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@@ -37,6 +38,7 @@ NODE_CLASS_MAPPINGS = {
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**CONDITION_SWITCHER_NODES,
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**LATENT_SWITCHER_NODES,
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**IMAGE_STROKE_NODES,
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**IMAGE_SPLITTER_NODES,
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**QWEN_MT_NODES,
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**ASPECT_RATIO_NODES,
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}
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@@ -56,6 +58,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"DD-ConditionSwitcher": "DD Condition Switcher",
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"DD-LatentSwitcher": "DD Latent Switcher",
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"DD-ImageStroke": "DD Image Stroke",
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"DD-ImageSplitter": "DD Image Splitter",
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"DD-QwenMTTranslator": "DD Qwen-MT",
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"DD-AspectRatioSelector": "DD Aspect Ratio Selector",
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}
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@@ -323,6 +323,38 @@
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}
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}
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},
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"DD-ImageSplitter": {
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"display_name": "DD Image Splitter",
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"description": "Split image by ratio and output specified part",
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"inputs": {
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"图像": {
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"name": "Image",
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"tooltip": "Input image to be split"
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},
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"切分方向": {
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"name": "Split Direction",
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"tooltip": "Choose split direction: horizontal (left-right) or vertical (top-bottom)"
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},
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"切分份数": {
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"name": "Split Count",
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"tooltip": "Number of parts to split the image into (2-10)"
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},
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"输出位置": {
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"name": "Output Position",
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"tooltip": "Select which part to output (starting from 1)"
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},
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"切分比例": {
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"name": "Split Ratio",
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"tooltip": "Split ratio, e.g., '1:1' for equal split, '2:1' for 2:1 ratio split"
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}
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},
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"outputs": {
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"0": {
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"name": "Image",
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"tooltip": "Split image at specified position"
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}
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}
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},
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"DD-VideoFrameExtractor": {
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"display_name": "DD Video Frame Extractor",
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"description": "Extract first or last frame from video",
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@@ -323,6 +323,38 @@
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}
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}
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},
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"DD-ImageSplitter": {
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"display_name": "DD 图像切分器",
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"description": "按比例切分图像并输出指定部分",
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"inputs": {
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"图像": {
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"name": "图像",
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"tooltip": "需要切分的输入图像"
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},
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"切分方向": {
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"name": "切分方向",
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"tooltip": "选择切分方向：左右切分或上下切分"
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},
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"切分份数": {
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"name": "切分份数",
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"tooltip": "将图像切分成多少份(2-10)"
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},
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"输出位置": {
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"name": "输出位置",
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"tooltip": "选择输出第几份切分的图像(1开始计数)"
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},
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"切分比例": {
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"name": "切分比例",
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"tooltip": "切分比例，如'1:1'表示均等切分，'2:1'表示2:1比例切分"
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}
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},
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"outputs": {
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"0": {
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"name": "图像",
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"tooltip": "切分后的指定位置图像"
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}
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}
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},
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"DD-VideoFrameExtractor": {
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"display_name": "DD 视频首尾帧输出",
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"description": "从视频中提取首帧或尾帧图像",
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@@ -0,0 +1,132 @@
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import torch
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import numpy as np
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from PIL import Image
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class DDImageSplitter:
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"""
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DD 图像切分器
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支持按比例切分图像并选择输出指定部分
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"""
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"图像": ("IMAGE",),
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"切分方向": (["左右", "上下"], {"default": "左右"}),
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"切分份数": ("INT", {"default": 2, "min": 2, "max": 10, "step": 1}),
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"输出位置": ("INT", {"default": 1, "min": 1, "max": 10, "step": 1}),
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"切分比例": ("STRING", {"default": "1:1", "multiline": False}),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("图像",)
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FUNCTION = "split_image"
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CATEGORY = "🍺DD系列节点"
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def split_image(self, 图像, 切分方向, 切分份数, 输出位置, 切分比例):
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"""
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切分图像并返回指定位置的部分
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"""
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# 确保输出位置在有效范围内
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if 输出位置 > 切分份数:
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输出位置 = 切分份数
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# 转换tensor到PIL Image
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image_tensor = 图像[0] if len(图像.shape) == 4 else 图像
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image_np = (image_tensor.cpu().numpy() * 255).astype(np.uint8)
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image_pil = Image.fromarray(image_np)
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width, height = image_pil.size
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# 解析切分比例
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ratios = self.parse_ratios(切分比例, 切分份数)
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if 切分方向 == "左右":
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# 左右切分
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split_image = self.split_horizontal(image_pil, ratios, 输出位置)
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else:
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# 上下切分
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split_image = self.split_vertical(image_pil, ratios, 输出位置)
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# 转换回tensor
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result_np = np.array(split_image).astype(np.float32) / 255.0
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result_tensor = torch.from_numpy(result_np).unsqueeze(0)
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return (result_tensor,)
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def parse_ratios(self, 切分比例, 切分份数):
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"""
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解析切分比例字符串
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"""
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try:
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# 解析比例字符串，如 "1:1" 或 "2:1:3"
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parts = 切分比例.strip().split(':')
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if len(parts) == 切分份数:
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ratios = [float(p) for p in parts]
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elif len(parts) == 2 and 切分份数 == 2:
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ratios = [float(parts[0]), float(parts[1])]
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else:
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# 如果比例数量不匹配，使用均等比例
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ratios = [1.0] * 切分份数
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except:
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# 解析失败时使用均等比例
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ratios = [1.0] * 切分份数
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# 标准化比例
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total = sum(ratios)
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return [r / total for r in ratios]
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def split_horizontal(self, image, ratios, 输出位置):
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"""
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水平切分（左右切分）
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"""
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width, height = image.size
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# 计算每部分的宽度
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widths = [int(width * ratio) for ratio in ratios]
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# 调整最后一个宽度以确保总和等于原宽度
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widths[-1] = width - sum(widths[:-1])
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# 计算切分位置的起始x坐标
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start_x = sum(widths[:输出位置-1])
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end_x = start_x + widths[输出位置-1]
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# 裁剪图像
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cropped_image = image.crop((start_x, 0, end_x, height))
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return cropped_image
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def split_vertical(self, image, ratios, 输出位置):
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"""
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垂直切分（上下切分）
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"""
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width, height = image.size
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# 计算每部分的高度
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heights = [int(height * ratio) for ratio in ratios]
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# 调整最后一个高度以确保总和等于原高度
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heights[-1] = height - sum(heights[:-1])
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# 计算切分位置的起始y坐标
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start_y = sum(heights[:输出位置-1])
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end_y = start_y + heights[输出位置-1]
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# 裁剪图像
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cropped_image = image.crop((0, start_y, width, end_y))
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return cropped_image
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# 节点类映射
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NODE_CLASS_MAPPINGS = {
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"DD-ImageSplitter": DDImageSplitter
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}
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# 节点显示名称映射
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NODE_DISPLAY_NAME_MAPPINGS = {
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"DD-ImageSplitter": "DD Image Splitter"
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}
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